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silicon valley season 7 - Cartesia eats pied piper's lunch? powered by Narrations 👀 - go.cartesia.ai/narrations

Played w Cartesia to narrate my blog post on, uh, AI—specifically, studying how AI apps have gone viral with teens on social media

gg

i accidentally left my coffee on top of my waymo

this is what we all wanted 🤝

There’s good reason stella has been referred to as “vibe coder final boss” in the group chat

🔊 🔥 The ultimate Voice AI Stack 🔥 🔊 "Hey, should I go speech-to-speech or stick with cascading architecture?" "What levers can I pull with my TTS provider?" "Is fine-tuning my LLM worth it for my voice use case?" Sound familiar? These are questions every voice AI builder

I'm so proud of what we built. Our tiny team of 3 beat one of the most well-funded startups - Character AI - to get real-time video chat to market. Available now for anyone to try.

Incredible product - try it out today!

the waymo cars drive out of the factory autonomously and immediately go to pick up riders in the Phoenix service area

full video about how @waymo superhuman driving works waymo founder Dmitri Dolgov at google i/o 2025

a mathematical habit I find useful for product thinking: in the limit, what does ... look like? for example, what will human-AI interaction look like in due time? then walk backwards from the limit and ask: how fast does it converge? how fast can you make it converge?

Yes - my advice to startups is prototype 10 product features - create an eval for 7 that don’t quite work yet and focus on 1 that users love. Then revisit the 7 with each new model release. In stark contrast to spending 3-6 months trying to make other features work reliably.

what part of the adoption curve is this?

theverge.com/tesla/691061/y… 👀

The future of software is going to be about managing the work that AI Agents are doing. The UX will be about task management, reviewing work, and orchestrating execution. A significant amount of the value will be packed into how the agent operates behind the scenes.

My hot take: PMs are the bottleneck in AI-first products b/c many engineers find "looking at the data" and doing evals "beneath" them PMs are more willing to do qualitative analysis on LLM traces, build theories of bad LLM behavior, aka evals---and evals are the bottleneck

The invention of modern writing instruments like the typewriter made writing easier, but they also led to the rise of writer’s block, where deciding what to write became the bottleneck. Similarly, the invention of agentic coding assistants has led to a new builder’s block, where

Official results are in - Gemini achieved gold-medal level in the International Mathematical Olympiad! 🏆 An advanced version was able to solve 5 out of 6 problems. Incredible progress - huge congrats to Thang Luong and the team! deepmind.google/discover/blog/…